Chemical bonds in organic molecules absorb energy in the near infrared region of the spectrum. Near infrared reflectance spectroscopy involves measuring the amount of light reflected by the substance to determine the amount of light being absorbed by the substance. Different types of carbon bonds absorb energy at different wavelengths. Determining the amount of light absorbed at a certain wavelength provides insight into which functional groups are in the substance and a quantitative measure of compounds containing these functional groups can be determined.
Near infrared spectroscopy is also employed in chemical imaging, and uses a tunable light source external to the experimental subject to determine its chemical composition. Typically, measurements can be made quickly on all types of samples.
Infrared thermometers have been used in agriculture for measuring temperatures and determining the need for the irrigation of crops. See, for example, U.S. Pat. Nos. 4,301,682 and 4,998,826.
Soybean (Glycine max (L.) Merr) is an important agricultural crop grown worldwide. Soybean comprises 52 percent of world oilseed production with 155.1 million metric tons, 46 percent of which were produced in the United States. In 1999, the United States produced 71.9 million metric tons on 29.9 million hectares. The importance of soybean continues to grow as new uses for soybean products are constantly being developed. Soybean has also long been a staple food in many diets. Uses of soybean range from industrial uses such as inks and lubricants to foods and food additives.
As the number of hectares of soybeans grown increases, so does the pressure exerted on soybean by the pathogen, Soybean Cyst Nematode (SCN) (Heterodera glycines Inchinohe). Currently, soybean growers practice crop rotation utilizing non-host species to reduce reproduction and populations of SCN. Genetic resistance to SCN has also been identified in soybean and implemented in soybean breeding programs for the development of SCN resistant soybean cultivars. While crop rotation is an effective measure in combating SCN, the use of SCN resistant soybean cultivars allows growers to increase soybean acreage without sacrificing yield to the SCN pathogen.
Breeding soybean for resistance to SCN involves the use of genetically resistant cultivars whose source of resistance is derived from plant introductions (PIs). Many of these PIs exhibit poor phenotypes. Crosses of these PI lines with agronomically desirable, but SCN susceptible phenotypes, result in populations of mixed resistant and susceptible genotypes.
Soybean cyst nematode was first characterized in Asia, but not discovered in the United States until 1954 (Winstead et al. 1955). Since its discovery in North Carolina, SCN has spread throughout all soybean-producing regions in the United States. Yield losses due to SCN in the United States were estimated at 7.6 million metric tons in 1998 (Wrather et al., 2000). This represented an increase of 1.6 million metric tons over 1998 estimates. Soybean cyst nematode is the most damaging pest of soybean today. It is a soil borne pest, which makes it able to spread with the movement of contaminated soil to uncontaminated soil via soil erosion or farm implements (Riggs, 1977).
Soybean cyst nematodes are prolific reproducers with each female being able to produce between 200 and 500 eggs. A cyst is formed by the SCN female to protect the eggs from the environment (Endo, 1964). Once the cyst is broken the eggs are released and they immediately begin to hatch if environmental conditions are conducive to nematode survival. The cysts are easily recognizable on the roots of host plants. Hosts of SCN include soybean, annual lespedeza (Kummerowia striate (Thunb.) H. & A.), common vetch (Vicia saliva L.), adzuki bean (Vigna angularis (Willd.) Ohwi & Ohashi), white lupine (Lupinus albus L.), and cowpeas (Vigna savi) (Epps and Chambers, 1962).
Plants are continually attacked by a diverse range of phytopathogenic organisms. These organisms cause substantial losses to all crops each year. Traditional approaches for control of plant diseases have been the use of chemical treatment and the construction of interspecific hybrids between resistant crops and their wild-type relatives as sources of resistant germplasm. However, environmental and economic concerns make chemical pesticides undesirable, while the traditional interspecific breeding is inefficient and often cannot eliminate the undesired traits of the wild species. Thus, the discovery of pest and pathogen-resistant genes provides a new approach to control plant disease.
Nematode infection is prevalent in many crops. Nematicides such as Aldicarb® and its breakdown products are known to be highly toxic to mammals. As a result, government restrictions have been imposed on the use of these chemicals.
Several genes responsible for disease resistance have been identified and isolated from plants. See Staskawicz et al. (1995) Science 268:661-667. Recently, the sugar beet Hsl.sup.pro-1 gene that confers resistance to the beet cyst nematode has been cloned. See Cai et al. (1997) Science 275:832-834; and Moffat (1997) Science 275:757. Transformation of plants or plant tissues with the resistance genes can confer disease resistance to susceptible strains. See, for example, PCT Publication WO 93/19181; and Cai et al. (1997) Science 275:832-834.
Near infrared spectroscopy (NIRS; 1000 to 3000 nm) has been used extensively for measuring moisture, protein, starch, and oil contents of seeds of several crop species (Osborne and Fearn, 1986). Plant breeders have successfully used NIRS to select individuals with superior seed or forage quality. However, selections based on genotypic markers have not been extensively tested. Traditionally, calibration equations are developed by correlating spectral data generated by NIRS, with reference data generated from substance analysis using wet chemistry. Calibration equations developed for the purpose of distinguishing genotypes must be based on reference values, which accurately characterize genotypic differences in the calibration population.
Rutherford (1998) examined the use of NIRS to determine resistance of sugarcane (Saccharum spp. hybrids) to stalk borer (Eldana saccharina Walker). Budscale extracts were used for NIRS analysis as well as analysis by high performance liquid chromatography (HPLC). Reference values were based on field bioassay measurements and resistance was categorized on a scale of one to nine. Limited success was obtained with the study in distinguishing resistance to stalk borer from susceptibility by using equations developed from modified partial least squares regression. An attempt to develop an equation based on one or few peaks using a forward stepwise multiple linear regression proved unsuccessful suggesting pathogen resistance is biochemically complex. It is also worth noting that in this study, prediction of stalk borer resistance in sugarcane based on NIRS was more accurate than prediction based on HPLC.
A study by Delwiche et al. (1999) also suggested the ability of NIRS to make genotypic distinctions. This study looked at the ability of NIRS to distinguish wheat (Triticum aestivum L.) lines containing wheat-rye (Secale cereale L.) translocations from lines that did not contain the translocation using ground seed. A discriminate analysis was performed on the spectral data to classify samples as either having the translocation or not having the translocation. Classification accuracy ranged from 78 to 99 percent. However, difficulties arose in correctly classifying near-isogenic lines differing only by the translocation and lines that were heterogeneous for the translocation.
Genetic resistance to SCN within soybean germplasm has emerged as the forerunner to overcoming this pathogen. While soybean breeders have had much success in developing SCN resistant germplasm, current methods for selecting this germplasm are labor and resource intensive. A challenge exists for identifying a method of screening germplasm for SCN resistance that does not significantly tax the resources of the modern soybean breeding program yet remains accurate in selecting desirable lines.
Current methodology for screening soybean (Glycine max (L.) Merr) genotypes for resistance to soybean cyst nematode (Heterodera gylcines Ichinohe) (SCN) involve the use of a labor and resource intensive bioassay that can provide inconsistent results due to heterogeneous populations of SCN. Thus, the development of near infrared spectroscopy (NIRS) as a monitoring and/or comparing system for screening soybean populations for SCN resistance would provide an improvement in the efficiency of the breeding process by saving time and money over current bioassay methods.